Global Economics - Senior

Course # ECON 4136

Credits 6

Prerequisites: Intermediate Microeconomics, Intermediate Macroeconomics and Econometrics One

Course Description

In this course we explore  contemporary economic issues in Central Asia. We introduce students to logic and instruments of analysis of national economies of the region. It starts with historical background of Central Asia and highlights region’s transition from planned to a market-based economy. The role of natural resources, migration, and remittances in the context of specific Central Asian republics is discussed in detail. Economic integration in the form of free trade, customs union and other types of regional cooperation is explored as well.

Course Learning Outcomes

Upon the completion of the course, students will be able to:

• Understand the nature of centrally planned economic system and its failure in former Soviet Union, particular in the context of all Central Asian republics.
• Assess and analyze costs associated with transition to a market-based economy in the region.
• Explain the role of natural resources in a country’s post-communist development and presence of any type of resource curse in Central Asia.
• Discuss the role of international migration from the region and remittances on a country’s development for the last two decades.
• Understand key economic challenges and main economic drivers and determinants of the national economies of the six Central Asian countries.
• Analyze regional cooperation projects among Central Asian republics and their possible integration into the world economy.

Course Assessments and Grading

Course # EAES 2130E

Credits 3

TBA

Course # ECON 3153E

Credits 3

TBA

Course # ECON 3136E

Credits 6

Prerequisites: N/A

Course Description

This course introduces students to the global business environment and the complexities managers face in developing international strategies. Students engage with the key theories of international business, the role of global institutions, trade, investment flows, and strategic choices made by firms operating across borders. Through case studies, group projects, and applied exercises, students explore globalization, international strategy, and global management practices in dynamic economic, cultural, and institutional contexts.

Course Learning Outcomes 

Upon the completion of the course, students will be able to:

• Explain and critically assess the major institutions of international business and their impact on global operations.
• Analyze regional, cultural, and institutional differences and their implications for managerial decision-making.
• Apply international business theories and frameworks to evaluate real-world cases.
• Formulate entry strategies and competitive approaches for firms in international markets.
• Assess key operational areas of international business including organization, supply chain, information systems, and HR management.
• Demonstrate collaborative problem-solving and effective communication in multicultural teams.

Course Assessments and Grading

Course # ECON 3031E

Credits 3

TBA

Course # DMNS 4186E

Credits 6

Prerequisite: Linear Algebra

Course Description

Linear programming is one of the most versatile and powerful mathematical programming techniques that can be employed for efficiently solving a stylized class of decision problems.

Linear programming has been used with marked success to solve optimization problems in areas such as economics (including banking and finance), business administration and management, agriculture and energy, contract bidding, nutrition (diet) planning, health care, public decision making, facility location, transportation, strategic planning, and so on.

In this course, students will study mathematics that deals with various real-world situations which leads to mathematical models involving linear optimization problems, geometrical solutions of two-variable problems, simplex algorithm, dual problems, sensitivity analysis and transportation problems.

Course Learning Outcomes

Upon the completion of the course, students will be able to:

• Formulate a mathematical model of real-life problems.
• Solve the formulated mathematical problem with the use of different algorithms.
• Translate the results back into the context of the original problem.
• Solve linear programming problems with R studio.

Course Assessments and Grading

Course # EAES 4751E

Credits 6

Prerequisites and/or Corequisites:  Information Technology course

Course Description

Programming in Python is an introductory course that covers programming techniques and tools to manipulate, manage, and analyze relevant data. The course focuses on the Python programming language that students will use to solve statistical analysis and GIS problems, apply Machine Learning and Deep Learning techniques, and create a website using Django framework. The tasks will be accomplished by identifying and using existing Python packages as well as appropriate open-source software extensions. The course introduces basic to advanced statistical functions, data visualization, and data manipulation techniques. The relevant functions in data science are explained. The main goal of this course is to give students an understanding of the breadth of different programming applications. In particular, students will be taught how to design and write effective code using Python to perform routine and specialized data manipulation, management, statistical analysis, GIS analysis, and web application development tasks.

Course Learning Outcomes

Upon completion of this course, every student will be able to:

• Explain the theoretical concepts of different data types
• Conceptualize and create loops and if/else statements in Python
• Create specialized functions in Python to handle results
• Manipulate data for descriptive statistical analysis in Python
• Use Django framework for development of different types of websites, in particular, a highly customizable app, such as an internet magazine website
• Use special packages, such as panda, to create graphs and convert plain text to formatted text.
• Using the packages NumPy, Matplotlib, Pandas and Skikit-Learn for various mathematical calculations, data manipulation, graphing and creating machine learning algorithms.
• Course Assignments and Grading

Course # ECON 3126E

Credits 6

Pre-requisites: Accounting, Financial Economics

Course Description

Financial Management develops the knowledge and skills expected of a finance manager. It equips students to identify and evaluate the investment, financing and dividend decisions required to support organisational strategy. The course introduces the role and purpose of the finance function and examines the economic environment in which financial decisions are made. Building on this foundation, students learn to analyse working-capital and long‑term investment decisions, evaluate sources and costs of finance, and understand how financing choices and the cost of capital affect business value. The syllabus also explores principles of business and asset valuation and the nature of financial risk, preparing candidates for further study in advanced financial management.

Course Learning Outcomes

Upon the completion of the course, students will be able to:

• Explain the purpose and objectives of financial management and its links to strategy.
• Analyse the economic and financial environment that affects financial decision‑making.
• Design and evaluate working‑capital policies for inventory, receivables, payables and cash.
• Apply discounted‑cash‑flow and other appraisal techniques to evaluate long‑term investments, considering inflation, taxation and risk.
• Evaluate sources of finance and estimate cost of capital, discussing capital‑structure considerations.
• Conduct business and asset valuation and understand efficient‑market implications.
• Identify financial risks (foreign‑exchange and interest‑rate) and apply hedging techniques.
• Use digital tools to gather, analyse and present financial information professionally.

Course Assessment and Grading

Course # ECON 3003

Credits 6

Course Description

This course provides an introduction to the main anthropological approaches to economic life, emphasizing intricate relationships between culture, society, and economics. The first part of the course provides an overview of anthropology and classical analytical frameworks for understanding how people live and organize their social lives in different ways. The subsequent part discusses contemporary issues surrounding value creation and contestation. Students should be aware that this course is not intended to be an economics course, but it looks at the economic aspects of human life from an anthropological perspective. The course is grounded in the comparative and ethnographically-based discipline of anthropology - it brings together a wide range of regional, cultural and historical material. We examine traditional non-market economies, gift giving and commodity exchange, state and alternative currencies, and human and posthuman economies. Thus, the course aims to explore the economy of societies, which integrates both formal, informal/ traditional ones embedded in the culture of the respective society. By the end of the course, students will have a nuanced understanding of how anthropological theories can help and offer insights into the interaction between human societies, their culture and mode of economy.

Course Learning Outcomes

Upon the completion of the course, students will be able to:

• - analyze and discuss the core concepts and principles of economic anthropology

  - apply concepts of cultural variation and the diversity of perspectives, practices, and beliefs found within each culture

  - Critically examine traditional and modern economic systems, focusing on how cultural patterns influence consumption and economic structures

  - Apply anthropological research methods such as participant observation, thick description, fieldwork, and interviewing to investigate and analyze economic practices, including production, exchange, distribution, and consumption, in relation to their cultural, social, and global contexts

Course Assessments and Grading